69 citations · 72 across the 4 of their papers we have counts for
4 papers
Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off
Zichen Zhang, Johannes Kirschner, Junxi Zhang +4
A default assumption in reinforcement learning (RL) and optimal control is that observations arrive at discrete time points on a fixed clock cycle. Yet, many applications involve c…
An Elementary Proof that Q-learning Converges Almost Surely
Matthew T. Regehr, Alex Ayoub
Watkins' and Dayan's Q-learning is a model-free reinforcement learning algorithm that iteratively refines an estimate for the optimal action-value function of an MDP by stochastica…
Randomized Exploration for Reinforcement Learning with General Value Function Approximation
Haque Ishfaq, Qiwen Cui, Viet Nguyen +5
We propose a model-free reinforcement learning algorithm inspired by the popular randomized least squares value iteration (RLSVI) algorithm as well as the optimism principle. Unlik…
Model-Based Reinforcement Learning with Value-Targeted Regression
Alex Ayoub, Zeyu Jia, Csaba Szepesvari +2
This paper studies model-based reinforcement learning (RL) for regret minimization. We focus on finite-horizon episodic RL where the transition model belongs to a known family…